Data Manipulation with R

• About this course

• Acknowledgements

• Introduction
• Introduction to tidyverse
• Data objects
• Readr
• tbl_df class
• The pipe operator
• Data manipulation
• Select
• Filter
• Arrange
• Mutate
• Summarise
• Grouping Data
• At, All, Each
• Generic do
• Combining Data
• Tidying Data
• Tidy Data with tidyr
• Handling missing values
• Working with backend engines
• RSQLite
• sparklyr
• dplyrXdf
• datatable
• Managing special formats
• Managing dates with lubridate
• Managing strings

Acknowledgements

I have taken efforts in writing this manual. However, it would not have been possible without the kind support and help of many individuals. I would like to extend my sincere thanks to all of them.

I would like to thank my colleagues, Nicola Sturaro, Enrico Tonini and Veronica Giro, for their contributions and for the long hours they spent checking and reviewing my messy writing.

I would finally like to express my special gratitude to Hadley Wickham for providing and sharing his research on the R package dplyr. Without his contribution, most parts of this manual would never have been written.

Andrea Spanò,
Quantide s.r.l.